Pay Attention to What Matters
Fuente:
arXiv
Guardado en:
| Autores principales: | Silva, Pedro Luiz, de Domenico, Antonio, Maatouk, Ali, Ayed, Fadhel |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
TeleMath: A Benchmark for Large Language Models in Telecom Mathematical Problem Solving
por: Colle, Vincenzo, et al.
Publicado: (2025)
por: Colle, Vincenzo, et al.
Publicado: (2025)
Large Language Models for Telecom: Forthcoming Impact on the Industry
por: Maatouk, Ali, et al.
Publicado: (2023)
por: Maatouk, Ali, et al.
Publicado: (2023)
TeleTables: A Benchmark for Large Language Models in Telecom Table Interpretation
por: Ezzakri, Anas, et al.
Publicado: (2025)
por: Ezzakri, Anas, et al.
Publicado: (2025)
Hermes: A Large Language Model Framework on the Journey to Autonomous Networks
por: Ayed, Fadhel, et al.
Publicado: (2024)
por: Ayed, Fadhel, et al.
Publicado: (2024)
Don't Pay Attention
por: Hammoud, Mohammad, et al.
Publicado: (2025)
por: Hammoud, Mohammad, et al.
Publicado: (2025)
Pay Attention to What You Need
por: Gao, Yifei, et al.
Publicado: (2023)
por: Gao, Yifei, et al.
Publicado: (2023)
Telecom Language Models: Must They Be Large?
por: Piovesan, Nicola, et al.
Publicado: (2024)
por: Piovesan, Nicola, et al.
Publicado: (2024)
What Matters in Transformers? Not All Attention is Needed
por: He, Shwai, et al.
Publicado: (2024)
por: He, Shwai, et al.
Publicado: (2024)
Pay Attention to Real World Perturbations! Natural Robustness Evaluation in Machine Reading Comprehension
por: Wu, Yulong, et al.
Publicado: (2025)
por: Wu, Yulong, et al.
Publicado: (2025)
Paying More Attention to Source Context: Mitigating Unfaithful Translations from Large Language Model
por: Zhang, Hongbin, et al.
Publicado: (2024)
por: Zhang, Hongbin, et al.
Publicado: (2024)
Pay What LLM Wants: Can LLM Simulate Economics Experiment with 522 Real-human Persona?
por: Choi, Junhyuk, et al.
Publicado: (2025)
por: Choi, Junhyuk, et al.
Publicado: (2025)
HPO: Hysteretic Policy Optimization for Stable and Efficient Training under Sparse-Reward Regime
por: Sana, Mohamed, et al.
Publicado: (2026)
por: Sana, Mohamed, et al.
Publicado: (2026)
Would a Large Language Model Pay Extra for a View? Inferring Willingness to Pay from Subjective Choices
por: Reusens, Manon, et al.
Publicado: (2026)
por: Reusens, Manon, et al.
Publicado: (2026)
Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse
por: Phi, Khiem, et al.
Publicado: (2024)
por: Phi, Khiem, et al.
Publicado: (2024)
What Matters For Safety Alignment?
por: Li, Xing, et al.
Publicado: (2026)
por: Li, Xing, et al.
Publicado: (2026)
Attention Basin: Why Contextual Position Matters in Large Language Models
por: Yi, Zihao, et al.
Publicado: (2025)
por: Yi, Zihao, et al.
Publicado: (2025)
SoK: Measuring What Matters for Closed-Loop Security Agents
por: Khurana, Mudita, et al.
Publicado: (2025)
por: Khurana, Mudita, et al.
Publicado: (2025)
MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering
por: Chen, Jialin, et al.
Publicado: (2025)
por: Chen, Jialin, et al.
Publicado: (2025)
What Matters for Model Merging at Scale?
por: Yadav, Prateek, et al.
Publicado: (2024)
por: Yadav, Prateek, et al.
Publicado: (2024)
Measuring What Matters -- or What's Convenient?: Robustness of LLM-Based Scoring Systems to Construct-Irrelevant Factors
por: Walsh, Cole, et al.
Publicado: (2026)
por: Walsh, Cole, et al.
Publicado: (2026)
Which Attention Heads Matter for In-Context Learning?
por: Yin, Kayo, et al.
Publicado: (2025)
por: Yin, Kayo, et al.
Publicado: (2025)
What Matters in Linearizing Language Models? A Comparative Study of Architecture, Scale, and Task Adaptation
por: Haller, Patrick, et al.
Publicado: (2025)
por: Haller, Patrick, et al.
Publicado: (2025)
Structured Attention Matters to Multimodal LLMs in Document Understanding
por: Liu, Chang, et al.
Publicado: (2025)
por: Liu, Chang, et al.
Publicado: (2025)
What Generative Artificial Intelligence Means for Terminological Definitions
por: Martín, Antonio San
Publicado: (2024)
por: Martín, Antonio San
Publicado: (2024)
Weaker LLMs' Opinions Also Matter: Mixture of Opinions Enhances LLM's Mathematical Reasoning
por: Chen, Yanan, et al.
Publicado: (2025)
por: Chen, Yanan, et al.
Publicado: (2025)
Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts
por: Zhang, Buze, et al.
Publicado: (2026)
por: Zhang, Buze, et al.
Publicado: (2026)
How to Connect Speech Foundation Models and Large Language Models? What Matters and What Does Not
por: Verdini, Francesco, et al.
Publicado: (2024)
por: Verdini, Francesco, et al.
Publicado: (2024)
"Sorry, I Didn't Catch That": How Speech Models Miss What Matters Most
por: Zhou, Kaitlyn, et al.
Publicado: (2026)
por: Zhou, Kaitlyn, et al.
Publicado: (2026)
Every Attention Matters: An Efficient Hybrid Architecture for Long-Context Reasoning
por: Ling Team, et al.
Publicado: (2025)
por: Ling Team, et al.
Publicado: (2025)
Optimizing What Matters: AUC-Driven Learning for Robust Neural Retrieval
por: Sheikholeslami, Nima, et al.
Publicado: (2025)
por: Sheikholeslami, Nima, et al.
Publicado: (2025)
Forget What Matters, Keep the Rest: Selective Unlearning of Informative Tokens
por: Koh, Seunghee, et al.
Publicado: (2026)
por: Koh, Seunghee, et al.
Publicado: (2026)
Structured Thinking Matters: Improving LLMs Generalization in Causal Inference Tasks
por: Sun, Wentao, et al.
Publicado: (2025)
por: Sun, Wentao, et al.
Publicado: (2025)
SignAttention: On the Interpretability of Transformer Models for Sign Language Translation
por: Bianco, Pedro Alejandro Dal, et al.
Publicado: (2024)
por: Bianco, Pedro Alejandro Dal, et al.
Publicado: (2024)
MindGYM: What Matters in Question Synthesis for Thinking-Centric Fine-Tuning?
por: Xu, Zhe, et al.
Publicado: (2025)
por: Xu, Zhe, et al.
Publicado: (2025)
MSWA: Refining Local Attention with Multi-ScaleWindow Attention
por: Xu, Yixing, et al.
Publicado: (2025)
por: Xu, Yixing, et al.
Publicado: (2025)
Affine-Scaled Attention: Towards Flexible and Stable Transformer Attention
por: Bae, Jeongin, et al.
Publicado: (2026)
por: Bae, Jeongin, et al.
Publicado: (2026)
Fine-grained Claim-level RAG Benchmark for Law
por: Das, Souvick, et al.
Publicado: (2026)
por: Das, Souvick, et al.
Publicado: (2026)
ReAttention: Training-Free Infinite Context with Finite Attention Scope
por: Liu, Xiaoran, et al.
Publicado: (2024)
por: Liu, Xiaoran, et al.
Publicado: (2024)
AttentionRAG: Attention-Guided Context Pruning in Retrieval-Augmented Generation
por: Fang, Yixiong, et al.
Publicado: (2025)
por: Fang, Yixiong, et al.
Publicado: (2025)
Attention Editing: A Versatile Framework for Cross-Architecture Attention Conversion
por: Cheng, Zhen, et al.
Publicado: (2026)
por: Cheng, Zhen, et al.
Publicado: (2026)
Ejemplares similares
-
TeleMath: A Benchmark for Large Language Models in Telecom Mathematical Problem Solving
por: Colle, Vincenzo, et al.
Publicado: (2025) -
Large Language Models for Telecom: Forthcoming Impact on the Industry
por: Maatouk, Ali, et al.
Publicado: (2023) -
TeleTables: A Benchmark for Large Language Models in Telecom Table Interpretation
por: Ezzakri, Anas, et al.
Publicado: (2025) -
Hermes: A Large Language Model Framework on the Journey to Autonomous Networks
por: Ayed, Fadhel, et al.
Publicado: (2024) -
Don't Pay Attention
por: Hammoud, Mohammad, et al.
Publicado: (2025)